Execution of Multi-Perspective Declarative Process Models Using Complex Event Processing

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Execution of Multi-Perspective Declarative Process Models Using Complex Event Processing
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CC Attribution 4.0 International:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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2021
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English

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Abstract
The Internet of Things (IoT) enables continuous monitoring of phenomena based on sensing devices as well as analytics opportunities in smart environments. Complex Event Processing (CEP) comprises a set of techniques for making sense of the behavior of a monitored system by deriving higher level knowledge from lower level system events. Business Process Management (BPM) attempts to model processes and ensures that executed processes con-form with a predefined sequence. In IoT scenarios frequently a large number of events has to be analyzed in real-time to allow an instant response. While BPM reaches its limits in such situ-ations, CEP is able to analyze and process high volume streams of data in real-time. The evaluation and execution of rules and models of both paradigms are currently based on separate formalisms and are frequently implemented in heterogeneous systems. The presented paper integrates both domains by proposing an execution approach for multi-perspective declarative process process models completely based on CEP. The efficiency of the combined paradigms is validated in an implemented demonstration with simulated and real-life sensor data.
Keywords Process Execution Complex Event Processing MP-Declare Event-Driven Systems

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